Spread-spectrum communication systems are well known in the art and widely deployed. A class of receivers well suited for use in spread-spectrum systems—such as those standardized in IS-95, IS-2000 (cdma2000), and the 3rd-Generation Partnership Project's (3GPP) Wideband Code-Division Multiple Access (W-CDMA) specifications—is the linear interference-whitening (LIW) receiver. LIW receivers suppress interference in addition to collecting signal energy for detection. One form of the LIW receiver is a transversal chip equalizer; another is a G-Rake receiver. The Rake receiver derives its name from its rake-like structure, wherein multiple receiver “fingers” are used to receive multiple signal images in a received multipath signal. By coherently combining the finger outputs in a weighted Rake combiner, the conventional Rake receiver can use multipath reception to improve the Signal to Interference-plus-Noise Ratio (SINR) of the received signal. A Generalized Rake (G-Rake) receiver improves interference suppression performance over a conventional Rake receiver using more sophisticated generation of the combining weights.
Recently, 2×2 Multiple-Input Multiple-Output (MIMO) technology has been standardized in Release 7 of the 3GPP specifications. The standardized scheme, referred to as Dual-Transmit Adaptive Arrays (D-TxAA), is similar to selective per-antenna rate control (S-PARC), except that adaptive unitary precoding is applied to each of the data streams, in this case to each of one or two High-Speed Downlink Shared Channel (HS-DSCH) data streams.
D-TxAA can be viewed as an extension of the previously standardized closed-loop mode-1 (CL-1) transmit diversity scheme, in that the precoding vectors (which map a data stream to the multiple transmit antennas) used for each of the D-TxAA data streams are selected from the same codebook used for CL-1. In contrast to CL-1, however, D-TxAA includes two modes of operation—single-stream mode and dual-stream mode. In single-stream mode, one of the four possible preceding vectors from the CL-1 codebook is applied to a single data stream. In dual-stream mode, orthogonal pairs of preceding vectors (again selected from the CL-1 codebook) are applied to the two data streams. The use of precoding has a significant impact on the receiver, and in particular complicates the design of LIW receivers such as Rake receivers.
Earlier versions of the 3GPP W-CDMA specifications (i.e., prior to Release 7) define two transmit diversity modes: CL-1, and an open-loop mode known as STTD. U.S. patent application Ser. No. 10/800,167 (Pub. No. US 2005/0201447), titled “Method and Apparatus for Parameter Estimation in a Generalized Rake Receiver,” filed Mar. 12, 2004 by Cairns et al. (the “Cairns application”), assigned to the assignee of the present application and incorporated herein by reference in its entirety, discloses a solution for G-Rake receivers in a transmit diversity system. The solution describes a parametric approach to estimating an impairment covariance matrix used to form G-Rake combining weights. The parametric approach estimates the impairment covariance as a sum of terms, including a separate term for each transmit antenna as well as a term corresponding to the sum of noise plus other-cell interference.
This solution works well for open-loop transmit diversity modes. In an open-loop mode, the impairments corresponding to each transmit antenna during a particular symbol period are uncorrelated, since different symbols are transmitted from the different antennas. In closed-loop mode, however, the mobile terminal specifies a phase offset, and the same symbol is transmitted by a primary antenna and simultaneously by a secondary antenna with the specified phase offset. In this case, the impairment due to each transmit antenna is highly correlated. This correlation may be exploited to improve interference suppression and receiver performance. U.S. patent application Ser. No. 11/751,109, titled “Receiver Parametric Covariance Estimation for Transmit Diversity,” filed May 21, 2007 by Jonsson et al. (the “Jonsson application”), assigned to the assignee of the present application and incorporated herein by reference in its entirety, discloses a parametric approach to estimating an impairment covariance matrix that accounts for the simultaneous transmission of the same symbols from a first and second antenna. In this approach the impairment covariance matrix for a system employing two transmit antennas is formulated as a sum of seven terms, including a term corresponding to each of the transmit antennas, a noise-plus-other-cell-interference term, plus four additional terms corresponding to the four possible precoding vectors in the CL-1 codebook. The terms are weighted by fitting parameters determined by fitting the parametrically modeled impairment covariance to a measured impairment covariance. An implicit assumption is that if one or more of the preceding vectors are not used by any user in the cell, then the corresponding fitting parameter will ideally be estimated as zero.
The CL-1 covariance estimation approach described in the Jonsson application applies to the transmission of only a single data stream, mapped according to a preceding vector to two (or more) antennas. In contrast, in D-TxAA, two data streams may be transmitted simultaneously, with both data streams sharing the same set of channelization codes. This creates additional self-interference, referred to as code-reuse interference, which affects the formulation of the impairment covariance. Code reuse is not accounted for in the formulation of Jonsson, since only one data stream is ever transmitted in CL-1.
Furthermore, in the solution described by Jonsson, an impairment term corresponding to each of the four possible preceding vectors in the CL-1 codebook is computed, since the receiver typically has no knowledge of which precoding vectors (except its own) are utilized by the transmitter. As mentioned above, if one or more of the preceding vectors is not actually utilized by at least one other same-cell user, then the fitting parameter corresponding to that term should ideally be estimated as zero. In this case, then, the impairment term is unnecessarily constructed. Because construction of the impairment terms is computationally demanding, any unnecessary construction of one or more impairment terms is undesirable. A related issue in a situation where one or more of the precoding vectors are not utilized is that the impairment covariance matrix is over-modeled, which may potentially lead to well-known problems with fitting parameter estimation and resulting poor performance.